Data Scientist

·        Must have at least 4–7 years of hands-on experience in data science or a related field, with a demonstrable track record of delivering machine learning solutions in production. ·        Should be proficient in Python and relevant data science libraries such as scikit-learn, PyTorch, or TensorFlow. · Knowledge of geospatial tools and frameworks such as GeoPandas, QGIS, PostGIS, or ArcGIS is a bonus. · Strong skills in SQL and experience with cloud data platforms (e.g. AWS, GCP, or Azure) are expected. ·        Must be familiar with the full ML lifecycle, from data wrangling and feature engineering through to model evaluation, deployment, and monitoring. ·        Must be comfortable with more advanced ML techniques such as ensemble learning, regularization, agent-based modelling, forecasting, etc. · Prior experience working with geospatial data and tools is strongly preferred, as is experience in domains involving demographic modeling, urban planning, or public sector analytics.